Job Application - Quantitative Analyst

Interview Sample Question

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Question I

I use daily OHLCV USDJPY data (from 2014-01-01 to 2017-01-20) and application of some models to forecast the highest and lowest price :

- Auto Arima models
- Exponential Time Series
- Univariate Garch models
- Exponential Weighted Moving Average
- Monte Carlo Markov Chain
- Bayesian Time Series
- Midas

For the staking model, I simply forecast the highest and lowest price, and then : 

- Kelly criterion and using highest or lowest price for closing transaction, otherwise using closing price if the forecasted lowest/highest price is not occur.
- Placed $100 an each of the forecasted variance value and do the settlement based on the real variance value. 

Kindly refer to Binary.com Interview Q1(Alternate link)

Here I wrote another extention page for Q1 which is analyse the data from minutes to daily. You are feel free to browse over Binary.com Interview Q1E.

Question II

Question III

Reference

Question I

1. Stock Market Forecasting Using LASSO Linear Regression Model
2. Using LASSO from lars (or glmnet) package in R for variable selection
3. Difference between glmnet() and cv.glmnet() in R?
4. Testing Kelly Criterion and Optimal f in R
5. Portfolio Optimization and Monte Carlo Simulation
6. Glmnet Vignette
7. lasso怎么用算法实现？
8. The Sparse Matrix and {glmnet}
9. Regularization and Variable Selection via the Elastic Net
10. LASSO, Ridge, and Elastic Net
11. 热门数据挖掘模型应用入门（一）: LASSO回归
12. The Lasso Page
13. Call_Valuation.R
14. Lecture 6 – Stochastic Processes and Monte Carlo
15. The caret Package
16. Time Series Cross Validation
17. Character-Code.com
18. Size Matters – Kelly Optimization

Question II

Question III

1. Data APIs/feeds available as packages in R